Kaushikan Dinakaran
@kaushikandinakaran
GenAI Engineer building RAG pipelines that automate enterprise workflows and improve compliant, accurate answers.
United StatesWhat I'm looking for
I’m a GenAI Engineer with mid-senior level expertise delivering AI-driven data solutions. At Wells Fargo, I developed end-to-end Retrieval-Augmented Generation (RAG) pipelines with OpenAI APIs, MySQL, and vector databases to anchor LLM responses to enterprise financial data—boosting relevance while ensuring compliance. I also engineered autonomous multi-agent systems in Python and LangChain to retrieve, extract, and validate complex internal documents, reducing manual effort and speeding up critical processing.
Earlier, as a Software Engineer, I architected an automated ingestion pipeline in Python using OpenAI APIs to process 545+ daily email status reports and store them in AWS Cloud Storage for immediate team access. I built an LLM-powered query bot and executive dashboards that eliminated manual report consolidation, cutting weekly reporting time by 90%, and I led migrations of legacy pipelines from AWS Lambda to Google Cloud Functions to reduce hosting costs by 15% and processing execution time by 30%. I’ve also delivered real-time streaming pipelines with Apache Kafka (up to 3 GB/min) and built scalable back-end applications with Python, Django, Celery, and Redis for platforms supporting 10M+ users, plus IoT-to-cloud real-time data collection experience that grounded my work in reliable data engineering.
Experience
Work history, roles, and key accomplishments
Developed end-to-end Retrieval-Augmented Generation (RAG) pipelines using OpenAI APIs, MySQL, and vector databases to improve enterprise answer relevance and ensure compliance with internal data standards. Built autonomous multi-agent systems to automate retrieval, extraction, and validation of complex internal documents, and optimized LLM workflows to reduce latency and improve accuracy for real-
Software Engineer
Think Future Technologies
Jan 2022 - Dec 2023 (1 year 11 months)
Architected an automated ingestion pipeline to process 545+ daily email status reports with Python and OpenAI APIs, storing results in AWS to eliminate manual entry. Built an LLM-powered query bot and dashboards to cut weekly report consolidation time by 90%, migrated legacy pipelines from AWS Lambda to Google Cloud Functions to reduce hosting costs by 15% and execution times by 30%, consolidated
Internet of Things Engineer
Disa Consulting Services (DCS)
Jul 2020 - Jun 2021 (11 months)
Engineered real-time data collection pipelines by integrating edge IoT devices and sensors to enable low-latency transmission for downstream cloud analytics. Developed hardware-to-cloud communication protocols to automate continuous data ingestion and establish a foundation for predictive modeling and machine learning workflows.
Education
Degrees, certifications, and relevant coursework
University of North Texas
Master, Data Science
2024 - 2025
Grade: GPA: 4/4
Master’s in Data Science with coursework in Applied Machine Learning for Data Scientists, Data Visualization and Communication, Introduction to Health Data Analytics, and Data Engineering. Recipient of the Oscar and Kaywin Blankemeyer Scholarship.
SRM University
Bachelor of Technology, Computer Science
2018 - 2022
Bachelor of Technology in Computer Science. Awarded a 90% Merit Scholarship for top-tier performance in the SRMJEEE.
Availability
Location
United StatesAuthorized to work in
Job categories
Skills
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